Become the expert needed to design secure and performant computer systems for smart digitalisation in society and the industry.
2 years (4 semesters)
English
120
August every year
About the study programme
Adoption of Artificial intelligence, and continued digitalisation, in both industry and society at large, requires increasingly complex computer systems. With a master’s in Computer Science, you become the expert needed to architect, develop, and deploy such systems and ensure their security and performance.
- Building on a bachelor’s in computer science, the master covers a broad range of more advanced topics, including network security and efficient data processing.
- You will learn to design and implement systems that utilize complex infrastructure, including the cloud, wireless networks and blockchain.
- Furthermore, you will also learn about the technology behind Artificial intelligence.
- The programme places a strong emphasis on practical skills, offering hands-on experience. You apply and extend your knowledge in programming assignments and course projects.
- You can write your master’s thesis in collaboration with industry, and participate in innovation and research.
Career prospects
Developers and researchers in Computer Science are indispensable in almost all industries. Some examples of businesses where they find employment: consulting companies, telecommunications companies, oil-related businesses, hospitals and other public agencies. We encounter digital technology everywhere, and researchers and developers in Computer Science are crucial in making information society and digitalization a reality.
A completed master’s degree in Computer Science provides the basis for admission to the PhD programme in Information technology, mathematics and physics.
Learning outcomes
All study programmes at the UiS have a set of defined learning targets. Read more about the learning outcome for this study programme.
After having completed the master’s programme in Computer Science, the student shall have acquired the following learning outcomes, in terms of knowledge, skills and general competences:
Knowledge
K1: Have advanced knowledge in Computer Science including Cloud computing, security, networks, distributed systems, data mining and machine learning.
K2: Have deep knowledge in the subject areas’ scientific theories and methods.
Skills
S1: Use relevant methods for research and software development in an independent manner.
S2: Analyse and relate in a critical manner to different information sources and apply these to structure and formulate professional reasoning within information technology.
S3: Perform an independent, limited research- or development project under guidance and in line with established ethical norms for research.
S4: Exploit knowledge in wireless communication, sensor networking, distributed communication systems, data mining and machine learning.
S5: Design, model, simulate, and develop advanced network-based computer systems with focus on dependability and security.
General Competence
G1: Analyse relevant professional, and research ethical problems.
G2: Apply one’s knowledge and skills to new areas to conduct complex tasks and projects.
G3: Communicate comprehensively about own work and master the subject area’s form of expression.
G4: Communicate professional problems, analyse, and draw conclusions within the subject area, both with specialists and the general public.
Study plan and courses
Enrolment year: 2025
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Specialisation for Engineering Students
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Compulsory courses
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Ethical Hacking
Year 1, semester 1
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Security and Vulnerability in Networks
Year 1, semester 1
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Cloud Computing Technologies
Year 1, semester 1
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Wireless Communications
Year 1, semester 1
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Distributed Systems
Year 1, semester 2
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Generative AI
Year 1, semester 2
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Algorithm Theory
Year 1, semester 2
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Master Thesis in Computer Science
Year 2, semester 3
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3rd semester at UiS or Exchange Studies
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Courses at UiS 3rd semester
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Choose one course
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Investment Analysis
Year 2, semester 3
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Project Management
Year 2, semester 3
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Recommended elective courses 3rd semester at UiS
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Discrete Simulation and Performance Analysis
Year 2, semester 3
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Data-intensive Systems and Engineering
Year 2, semester 3
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Information Retrieval and Text Mining
Year 2, semester 3
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Blockchain Technologies and Application
Year 2, semester 3
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Other elective courses 3rd semester at UiS
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Project in Computer Science
Year 2, semester 3
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Image Processing and Computer Vision
Year 2, semester 3
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Deep Neural Networks
Year 2, semester 3
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Statistical Modeling and Simulation
Year 2, semester 3
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Exchange 3rd semester
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Exchange Studies 3rd semester
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-
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Specialisation for Science Students
-
Compulsory courses
-
Ethical Hacking
Year 1, semester 1
-
Security and Vulnerability in Networks
Year 1, semester 1
-
Cloud Computing Technologies
Year 1, semester 1
-
Wireless Communications
Year 1, semester 1
-
Distributed Systems
Year 1, semester 2
-
Generative AI
Year 1, semester 2
-
Algorithm Theory
Year 1, semester 2
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Master Thesis in Computer Science
Year 2, semester 3
-
-
3rd semester at UiS or Exchange Studies
-
Courses at UiS 3rd semester
-
Choose one course
-
Investment Analysis
Year 2, semester 3
-
Project Management
Year 2, semester 3
-
-
Recommended elective courses 3rd semester at UiS
-
Discrete Simulation and Performance Analysis
Year 2, semester 3
-
Data-intensive Systems and Engineering
Year 2, semester 3
-
Information Retrieval and Text Mining
Year 2, semester 3
-
Blockchain Technologies and Application
Year 2, semester 3
-
-
Other elective courses 3rd semester at UiS
-
Project in Computer Science
Year 2, semester 3
-
Image Processing and Computer Vision
Year 2, semester 3
-
Deep Neural Networks
Year 2, semester 3
-
Statistical Modeling and Simulation
Year 2, semester 3
-
-
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Exchange 3rd semester
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Exchange Studies 3rd semester
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Academic requirements
A bachelor´s degree within the following disciplines is required:
- Computer Engineering
- Computer Science, Informatics or similar with at least 50 ECTS credits in computer science/computer engineering
Applicants must have the equivalent of 20 ECTS credits in mathematics or statistics
If you have completed studies/courses outside the University of Stavanger, you must upload course descriptions that have clearly defined curriculum (learning outcomes), together with your transcript of records. The course names and codes on the course descriptions must match the transcript of records. If you do not provide course descriptions, you might risk your application to not be prioritized.
The course descriptions should be submitted in English or in Norwegian, but a translation does not have to be provided by an authorized translator.
Admission to this master's programme requires a minimum grade average comparable to a Norwegian C (according to ECTS Standards) in your bachelor's degree. Applicants with a result Second-class lower Division or lower are not qualified for admission.
Application and admission
Contact
For inquiries regarding admission to international Master's programmes, send an email to: admissions@uis.no
Student life at UiS
Student exchange
By going on exchange to one of our partner institutions abroad as part of your studies, you will have an opportunity to get a unique education. In addition to improving your career opportunities, you grow as a person and gain the ability to greater reflect on the topics you study as part of your degree.
Schedule for the exchange
3rd semester
Students can go on a study abroad experience during the 3rd semester of the master's programme in Computer Science. Abroad, you must choose courses that provide an equivalent specialisation in your field of study, and these must be approved before you leave. It is also important that the courses you are going to take abroad do not overlap with courses you have already taken or will take later in your studies. It is recommended to think about your specialisation and/or your field of interest. You must choose at least one non-science/technological course equivalent to 5-10 ECTS (e.g. economics, languages, ethics, project management, green transition or similar).
More opportunities
In addition to the recommended universities listed below, UiS has a number of agreements with universities outside Europe that are applicable to all students at UiS, provided that they find a relevant course offering. Within the Nordic region, all students can use the Nordlys and Nordtek networks.
Contact your study adviser at the faculty if you have questions about guidance and pre-approval of courses: Sheryl Josdal
General questions about exchange:
Go to the exchange guide in the Digital student service desk
See where you can travel
Frequently asked questions
Questions about the study programme? Find more information here.
What do you learn when you choose the study programme Computer Science?
Master’s programme in Computer Science teaches you the management, design and programming of computer systems. The ability to integrate knowledge and skills in security, reliability and scalability together with algorithm theory and statistics is necessary to respond to challenges in computer systems in all industries.
The programme provides a basis for work with the development and planning of commercial computer systems for various purposes. You gain knowledge and skills in network security, reliability of distributed systems, simulation and modeling.
What do you learn when you choose the study programme Data Science?
Master’s programme in Data Science teaches you to extract relevant information from a compilation of large data sets from different sources. The ability to create, manage and utilize data has become one of the most important challenges for practitioners in almost all disciplines, sectors and industries.
Data Science provides a basis for work in data analysis and development of data processing systems for the entire data life cycle. You gain knowledge and skills in advanced statistics, data mining, machine learning and processing large amounts of data. The study will be highly sought after in the future labor market, with the development of smart solutions such as in smart cities, with smart energy and digitalisation.
Contact
Faculty Administration TN
Kontor for utdanningsadministrative tjenester
Department of Electrical Engineering and Computer Science